Multi-object Tracking under Occlusion Using Dual-Mode Graph Embedding

2013 ◽  
Author(s):  
Jin Gao ◽  
Junliang Xing ◽  
Weiming Hu ◽  
Xiaoqin Zhang ◽  
Ruiguang Hu
Keyword(s):  
Object Tracking ◽  
Graph Embedding ◽  
Dual Mode

Graph-Embedding-Based Learning for Robust Object Tracking

2014 ◽  
Vol 61 (2) ◽  
pp. 1072-1084 ◽  
Author(s):  
Xiaoqin Zhang ◽  
Weiming Hu ◽  
Shengyong Chen ◽  
Steve Maybank
Keyword(s):  
Object Tracking ◽  
Graph Embedding

Multiple-Object Tracking

2011 ◽  
Vol 58 (3) ◽  
pp. 196-200 ◽  
Author(s):  
K. Botterill ◽  
R. Allen ◽  
P. McGeorge
Keyword(s):  
Object Tracking ◽  
Cognitive Processes ◽  
Spatial Location ◽  
Multiple Object Tracking ◽  
Tracking Performance ◽  
Multiple Object

The Multiple-Object Tracking paradigm has most commonly been utilized to investigate how subsets of targets can be tracked from among a set of identical objects. Recently, this research has been extended to examine the function of featural information when tracking is of objects that can be individuated. We report on a study whose findings suggest that, while participants can only hold featural information for roughly two targets this task does not affect tracking performance detrimentally and points to a discontinuity between the cognitive processes that subserve spatial location and featural information.

Predictable paths increase the use of motion in object tracking

2010 ◽  
Author(s):  
Adriane E. Seiffert ◽  
Rebecca St. Clair
Keyword(s):  
Object Tracking

Location and identity are entangled in multiple-object tracking

2010 ◽  
Author(s):  
Todd S. Horowitz ◽  
Michael A. Cohen ◽  
Yair Pinto ◽  
Piers D. L. Howe
Keyword(s):  
Object Tracking ◽  
Multiple Object Tracking ◽  
Multiple Object
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